Design improvement of cooling channel layout for plastic injection moulding

The objective of this research is to propose a method for designing cooling channel layouts for plastic injection moulding; optimization techniques have been adopted to simultaneously reduce moulded defects and cooling cycle times. Using the numerical examples of coolant flow in cooling channels, it is found that curved cooling channels along the cavity significantly affect the temperature of the plastic. Moreover, the differences between cooling channels for 2-D and 3-D models are discussed. Furthermore, the cooling channel layout is designed in two stages on the basis of the results from the numerical examples. In the proposed design procedure, the cooling channel layout is determined after taking into consideration the design factors that are significant for maintaining the required plastic temperature.     

Inverse thermal mold design for injection molds

The thermal mold design and the identification of a proper cooling channel design for injection molds becomes more and more complex. To find a suitable cooling channel system with objective rules based on the local cooling demand of the part a new methodology for the thermal mold design based on an inverse heat transfer problem was introduced. Based on a quality function regarding production efficiency as well as part quality, additional aspects to model the injection molding process are discussed. Aim of those extensions is the improvement of the inverse optimization of the problem.     

Optimization of injection moulding conditions with user-definable objective functions based on a genetic algorithm

This paper applies a Genetic Algorithm (GA) method to optimize injection moulding conditions, such as melt temperature, mould temperature and injection time. A GA is very suitable for moulding conditions optimization where complex patterns of local minima are possible. Existing work in the literature has limited versatility because the optimization algorithm is hard-wired with specific objective function. However, for most of the practical applications, the appropriateness of optimization objective functions depends on each specific moulding problem. The paper develops a multi-objective GA optimization strategy, where the objective functions may be defined by the designers, including using different criteria and/or weights. For parts with general quality requirements, an objective function is also recommended with some quality measuring criteria, which are either more accurately represented or cover more moulding defects than those from existing simulation-based optimization approaches. The paper also elaborates on the effective GA attributes suited to moulding conditions optimization, such as population size, crossover rate and mutation rate. A case study demonstrates the effectiveness of the proposed approach and algorithm. The optimization results are compared with those from an exhaustive search method to determine the algorithm's accuracy in finding global optimum. It is found to be favourable.     

A hybrid of back propagation neural network and genetic algorithm for optimization of injection molding process parameters

This paper presents a hybrid optimization method for optimizing the process parameters during plastic injection molding (PIM). This proposed method combines a back propagation (BP) neural network method with an intelligence global optimization algorithm, i.e. genetic algorithm (GA). A multi-objective optimization model is established to optimize the process parameters during PIM on the basis of the finite element simulation software Moldflow, Orthogonal experiment method, BP neural network as well as Genetic algorithm. Optimization goals and design variables (process parameters during PIM) are specified by the requirement of manufacture. A BP artificial neural network model is developed to obtain the mathematical relationship between the optimization goals and process parameters. Genetic algorithm is applied to optimize the process parameters that would result in optimal solution of the optimization goals. A case study of a plastic article is presented. Warpage as well as clamp force during PIM are investigated as the optimization objectives. Mold temperature, melt temperature, packing pressure, packing time and cooling time are considered to be the design variables. The case study demonstrates that the proposed optimization method can adjust the process parameters accurately and effectively to satisfy the demand of real manufacture.     

Process Development and Product Quality of Micro-Metal Powder Injection Molding

Injection molding has been found to be an efficient and cost-effective manufacturing technique for the production of a wide variety of parts and components at both macro- and microscale. This is attributed to the application of robust design and process development. However, every manufacturing technique is challenged by quality issues and part defects, but tackled by continuous improvement framework(s). This systematic monitoring and control approach of dimensional accuracy, mechanical properties, and surface quality of the finished part strongly depend on process conditions at different production stage. Therefore, the aim of this study is to review process development of micro-metal injection molding; focusing on critical factors influencing part quality and optimization of process parameters. The critical factors that influenced the finished part quality are part design, mold design, material selection, machine, and process conditions. Optimizing mold temperature, melt temperature, injection speed, injection pressure, cooling time, packing, and holding parameters improve the quality of the molded part. This trend of process development of injection molding gave rise to a broad scope of applications with brighter future potentials for the next decades, particularly for medical and electronics applications.     

Integrated optimization of machine product design and process design

In order to attain the true integration of computer-aided design and computer-aided manufacturing not only is a smooth flow of information required, but also decision making for both product design and process design must be synthesized. In this paper an integrated design process is proposed in which decisions concerning both product design and process design are simultaneously made. According to the proposed design procedures, an integrated optimization problem is formulated. This optimization is expressed as a multiobjective optimization problem which produces many Pareto optimum solution sets corresponding to combinations of materials used for parts. The algorithm for solving the problem is also presented. The proposed method is applied to designing a cylindrical co-ordinate robot, thereby demonstrating the effectiveness of conducting a simultaneous process through product design and process design.     

Using hotspot analysis to establish non-equidistant cooling channels automatically

ABSTRACT

In the injection molding (IM) process, the primary factor that affects product quality and production cycle time is the position of cooling channels; thus, this study has proposed a non-equidistant cooling channel (CC). This was calculated based on the heat difference of the plastic product after filling. In any part of the surface with high temperature, channels (center) were constructed close to the product, whereby the affected area was relatively small. Conversely, channels (center) were built far from the product in parts with low temperature, with the affected area being relatively large. This study applied this idea and used a self-designed application programming interface (API) to automatically establish the paths of non-equidistant cooling channels. The proposed cooling channels were input to Moldflow, after being compared with conventional and conformal channels, the proposed channel successfully reduced the maximum average temperature and temperature differences, thereby effectively enhancing the cooling efficiency and product quality.     

Associativity modelling of a mould assembly for expandable polystyrene foam

The design and fabrication of a mould for expandable polystyrene (EPS) buffers involves an approach which is radically different from that associated with conventional plastic injection moulding. This is because the EPS mould design encompasses both the classical tooling specifications and considerations of the actual moulding process itself. This paper discusses the notion of associativity modelling in the CAD design of a mould assembly for the manufacture of EPS buffers. This modelling paradigm aims to integrate 5 mould design factors with 25 process (moulding) parameters. Through a better understanding of the interactions between design factors and process parameters, and among the process parameters themselves, a harmonious decision table can be derived which compromises the competing demands of factors and parameters. Because of the visibility of the interactions among parameters, the notion of associativity modelling offers the designer a better insight into mould assembly design, leading to practical mould design solutions that harmonize the functions of the different sub-assemblies.     

Feature-based integration of conceptual and detailed mould design

The plastic production industry has been growing rapidly in recent years, and injection mould, which is especially widely used in 4C (computer, communication, consumer electronics, and car) products, is the most popular in moulding plastic. The diverse requirements of customers and pressures of just-in-time production are big challenges in the injection mould industry. The advantages, that keep products’ quality and increase work efficiency, will decide a company's competitive capabilities. Therefore, this study proposes a feature-based integration of the conceptual and detailed mould design process within the computer-aided design (CAD) tool. It adopts a feature-oriented method and the dedicated application programming interface (API) to implement the features integration function of the conceptual and detailed mould design. Based on intellectualised, customised, and standardised procedures, not only does this prevent probable engineering mistakes and generate consistent web reports, but also transmits the intact feature information from conceptual to detailed mould design, thus shortening detailed mould design processes. In the case studies of this paper, using the feature-based navigating system can result in time savings up to 56% and 59%. The results show significant time savings over traditional mould design processes.     

THREE-DIMENSIONAL TRANSIENT MOLD COOLING ANALYSIS BASED ON GALERKIN FINITE ELEMENT FORMULATION WITH A MATRIX-FREE CONJUGATE GRADIENT TECHNIQUE

A methodology is presented to simulate the three-dimensional heat transfer within a mold during the injection molding process. The mold cooling analysis assists cooling channel design and paves the way for part shrinkage and warpage analysis. The transient temperature distributions in the mold and the polymer part are simultaneously computed by Galerkin Finite Element Method (GFEM) using a matrix-free Jacobi Conjugate Gradient (JCG) scheme. The numerical method presented here is efficient and has shown to require a fraction of the memory and computing time required by conventional methods. The matrix-free algorithm is initially validated using an injection mold designed to produce a plaque with a molded-in hole. Subsequently, the method is further applied to a representative automotive plastic component.     

Unification of robust design and goal programming for multiresponse optimization—a case study

Fixing the levels of input process parameters to meet a required specification of output is a common process quality control problem. Especially when the output has many quality characteristics, and each of these quality characteristics has to satisfy a given specification, difficulties may arise. One such problem was encountered in an injection moulding process. This process was optimized using Taguchi's Robust Design methodology. Details of the process, problems encountered and outcome of optimization are presented in this paper. The optimization study using Taguchi's methodology revealed that the optimum conditions obtained for one response are not completely compatible with those of other responses. So trade-offs were made in selection of levels for factors using engineering judgement. This increases the uncertainty in the decision making process. In this paper, an approach is presented to optimize multiresponses simultaneously using goal programming in conjunction with Taguchi's methodology. Details of modelling, analysis and inferences obtained with relevance to the case are presented. This study revealed that the optimum conditions obtained using goal programming in conjuction with Taguchi's methodology have better goal attainment properties compared to Robust design. To understand goal attainment behaviour of output characteristics for various process conditions, a detailed sensitivity analysis was also conducted. The outcome of this analysis is also discussed in this paper. © 1997 John Wiley & Sons, Ltd.     

Intelligent process design system for the transfer moulding of electronic packages

Currently, mould design and the setting of the process parameters of transfer moulding for electronic packages are done manually in a trial-and-error manner. The effectiveness of the setting of parameters is largely dependent on the experience of engineers. The paper describes an intelligent process design system for transfer moulding of electronic packages that is used to determine optimal mould design parameters and the setting of the process parameters mainly based on case-based reasoning, artificial neural networks and a multiobjective optimization scheme. The system consists of two modules: a case-based reasoning module and a process optimization module. The former module is used to determine initial mould design parameters and the setting of the process parameters while the latter module is used to determine optimal mould design parameters and the setting of the process parameters. Implementation of the intelligent system has demonstrated that the time for the determination of optimal mould design parameters and the setting of the process parameters can be greatly reduced, and the setting of parameters recommended by the system can contribute to the good quality of moulded packages.     

An intelligent hybrid system for initial process parameter setting of injection moulding

Currently, determination of the initial process parameter settings for injection moulding is mainly performed by moulding personnel, and the effectiveness of the parameter setting is largely dependent on the experience of these personnel. In this paper, an intelligent hybrid system, called HSIM, is described, which is used to determine a set of initial process parameters for injection moulding based on the artificial intelligence (AI) techniques, case-based reasoning (CBR), and hybrid neural network (NN) and genetic algorithm (GA). HSIM can determine a set of initial process parameters for injection moulding quickly, without relying on expert moulding personnel, from which moulded parts free from major moulding defects can be produced.     

纵向超声波辅助微注塑方法

微注塑过程中,聚合物熔体在微小腔体中流动时充模阻力比常规注塑大,这影响了熔体填充效果,同时热量损失的不均衡性和不确定性容易导致注塑精度不高．提出了纵向超声波辅助微注塑方法,并对超声波振动对聚合物熔体的作用机理进行了探讨,分析了超声换能器结构对应力、振幅和响应频率的影响．基于对微注塑过程的模拟结果,开发了纵向超声波辅助微注塑装置．通过在微注塑过程中纵向超声波对熔体的能量作用降低熔体黏度,改善了熔体流动和充填性能．为了验证超声波辅助微注塑的效果,进行了菲涅尔透镜实际注塑实验．实验结果表明,相同的注塑工艺条件下,超声辅助微注塑过程中聚合物熔体的充填性能提高了6．91％．     

新型鼠标底座注射成形流动仿真及模具设计

目的设计并制造出新颖、使用方便以及功能齐备的鼠标。方法采用3D打印技术打印了新型鼠标模型。在设计浇注系统的基础上,对新型鼠标底座的注射成形工艺流动过程进行了有限元仿真。分析了充填成形过程中的充填时间和冷却固化时间、体积收缩率与缩痕、塑件的变形情况、表层与心部的取向、残余应力以及气孔和熔接线等相关参数。结果成功完成了鼠标底座的注射成形模具的设计。结论采用3D打印技术与有限元模拟相结合的方法,来开发新型塑料制品,能有效节省设计时间、保证设计质量。     

快速热循环注塑成型技术发展综述

快速热循环注塑成型技术是一种绿色环保的新兴注塑成型技术。相比常规注塑成型技术,该技术可显著改善塑件表面质量,获得表面高光且无熔痕的塑料产品。采用快速热循环注塑技术可避免常规注塑过程中的后续喷涂工艺,从而降低生产成本,简化生产流程,缩短生产周期,所生产的塑件可直接用于产品装配。在具体技术和工艺研究两个方面详细介绍了快速热循环注塑技术。在具体技术方面,阐述了快速热循环注塑成型技术的工艺原理,介绍了模具快速加热与快速冷却的方法,以及随形加热与冷却管道的设计制造;在工艺研究方面,综述了快速热循环注塑数值模拟方面的研究,介绍了快速热循环注塑工艺改善产品质量的内在机理。最后,分析了快速热循环注塑技术依然存在的问题,并对其未来的发展趋势进行了展望。     

Wirkmedienbasierte Herstellung hybrider Metall‐Kunststoff‐Verbundbauteile mit Kunststoffschmelzen als Druckmedium

Working media based manufacturing of hybrid metal‐plastic‐compounds by using thermoplastic melt as pressurized media This paper presents an alternative manufacturing process for metal plastic hybrid parts. The focus is placed on the integration of injection moulding technology with hydroforming technology. The forming of bulging geometry and cup geometry from Aluminium and Steel sheets was examined. Particularly, the process parameters involved in forming such geometries including Injection pressure, volume flow rate, were measured, and their influence on the final shape of product as well on the strain distribution was analyzed.     

Failure analysis of H13 working die used in plastic injection moulding

The present study is focused on the failure of a die used in plastic injection moulding. The die was made from AISI H13 steel and was intended for the production of plastic cups used for the outer closure of cylindrical aluminium cans in coffee packaging. The appearance of the die provides a clear picture of degradations. Extended corrosion damage on various areas of the metallic part and a wide crack can be observed by the naked eye. Hardness measurements and chemical analysis eliminated the probability of faulty material selection or improper heat treatment. Visual inspection, macro-examination and microscopic observations of representative failed parts revealed that the failure was caused by corrosion that led to the total cracking of the die. The design deficiency and improper cooling conditions generated a complex fatigue-corrosion cracking mechanism that lead to the damage of the die after half of it’s predicted service life.     

A hybrid of mode-pursuing sampling method and genetic algorithm for minimization of injection molding warpage

This paper presents a hybrid optimization method for minimizing the warpage of injection molded plastic parts. This proposed method combines a mode-pursuing sampling (MPS) method with a conventional global optimization algorithm, i.e. genetic algorithm, to search for the optimal injection molding process parameters. During optimization, Kriging surrogate modeling strategy is also exploited to substitute the computationally intensive Computer-Aided Engineering (CAE) simulation of injection molding process. With the application of genetic algorithm, the “likelihood-global optimums” are identified; and the MPS method generates and chooses new sample points in the neighborhood of the current “likelihood-global optimums”. By integrating the two algorithms, a new sampling guidance function is proposed, which can divert the search process towards the relatively unexplored region resulting in less likelihood of being trapped at the local minima. A case study of a food tray plastic part is presented, with the injection time, mold temperature, melt temperature and packing pressure selected as the design variables. This case study demonstrates that the proposed optimization method can effectively reduce the warpage in a computationally efficient manner.     

Tolerance analysis and synthesis for cam mechanisms

Tolerance is one of the most important parameters in product and process design, so tolerancing plays a key role in design and manufacturing. Tolerance synthesis is in a period of extensive study due both to increased demands for quality products and to increasing automation of machining and assembly. Optimum tolerance design and synthesis ensures good quality product at low cost. This paper presents an analytical methodology for tolerance analysis and synthesis for a disk cam-translating follower system. Both dimensional ( size) and geometric tolerances ( position and profile ) on the components are considered. Tolerance analysis is performed on individual tolerances as well as on total tolerance accumulation. With the lowest manufacturing cost as its objective function a nonlinear optimization model is formulated for tolerance synthesis and solved by a sequential quadratic programming ( SQP) algorithm. An example is provided to illustrate the optimization model and solution procedure.